Polarization SAR image compression method based on multi-direction dictionary learning

Abstract

The invention discloses a polarization SAR image compression method based on multi-direction dictionary learning. The method mainly solves the problem that the quality of an image compressed and reconstructed through the existing technology is low. The method includes the implementation steps of firstly, inputting a set of polarization SAR four-channel images, and conducting asymmetrical three-dimensional wavelet transform; secondly, conducting sparse representation on coefficient matrixes, in different directions, of high-frequency sub-bands under different scales of all the channels after the discrete wavelet transform is conducted so as to obtain all sparse matrixes; thirdly, conducting quantizing and coding on the coefficient matrixes of all low-frequency sub-bands after the discrete wavelet transform is conducted to obtain low-frequency code streams; fourthly, conducting unified quantizing and coding on the sparse matrixes in different scales and different directions so as to obtain high-frequency code streams; fifthly, forming final code streams through the low-frequency code streams and the high-frequency code streams. By means of the method, redundancy between the channels can be effectively eliminated, the marginal information and contour information of images are better preserved, the quality of a compressed and reconstructed image is improved, and the method can be used for transmitting and storing polarization SAR images.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a polarimetric synthetic aperture radar (SAR) image compression method, which can be used for transmission and storage of polarimetric SAR images. Background technique [0002] Synthetic Aperture Radar (SAR), as a high-resolution microwave remote sensing tool, has all-weather and all-time imaging characteristics, contains a large number of signal features, and is widely used in remote sensing fields, such as military reconnaissance, terrain mapping, and target recognition. Polarization synthetic aperture radar (SAR) provides more information than traditional synthetic aperture radar, and greatly enhances the ability to process information. But the corresponding amount of data will increase exponentially. Since large-capacity data needs to be transmitted and stored in real time, data compression is particularly necessary. [0003] The traditional polarimetric SAR ...

AI Technical Summary

Problems solved by technology

Although this method takes into account and effectively removes the redundancy between polarization channels, when the compression rate is constant, the SPIHT algorithm cannot effectively retain the edge information and contour information of the image, resulting in a decrease in the quality of the reconstructed image

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